Enterprise Knowledge Management and Conceptual Modelling

Abstract

Turbulence is in the nature of business environments. Changes brought about because of different requirements such as social, political, technical and economic, exert pressures on organisations to respond in a timely and cost effective way to these challenges. In such an unstable environment information system developers are challenged to develop systems that can meet the requirements of modern organisations.

In this decade organisations also experience the effects of the integration and evolution of Information Technology (IT). While information systems continue to serve traditional business needs such as co-ordination of production and enhancements of services offered, a new and important role has emerged namely the potential of such systems in adopting a more supervisory and strategic support role. These developments offer opportunities for changes to organisational structures and the improvement of business processes. The traditional approach to information systems development has proved to be too monolithic and lacking facilities for dealing with highly complex, multidimensional, and distributed systems. In the traditional paradigm little attempt is made in understanding how the proposed system relates to other components (some of which may be legacy systems themselves) or the effect that the system will have on the enterprise itself. This paper advances a position, based on research work and the application of this work on many industrial and commercial applications, which states that ‘the single most important factor to successful business evolution through the use of information technology is Enterprise Knowledge Management’. Enterprise Knowledge Management involves many facets of the information systems domain including technical (business processes, flow of information etc), organisational and social (policies, structures and work roles etc) and teleological (purposes and reasons) considerations. Conceptual modelling plays a central role in the way that one can capture, reason, represent, use for agreement between many stakeholders and discover new knowledge from legacy systems.